Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

The molecular mechanism of verbascoside(OC1) in promoting acetylcholine(ACh) release in the pathogenesis of Alzheimer's disease(AD) was studied. Adrenal pheochromocytoma cells(PC12) of rats induced by β-amyloid protein(1-42)(Aβ_(1-42)) were used as AD models in vitro and were divided into control group, model group(Aβ_(1-42) 10 μmol·L~(-1)), OC1 treatment group(2 and 10 μg·mL~(-1)). The effect of OC1 on phosphorylated proteins in AD models was analyzed by whole protein phosphorylation quantitative omics, and the selectivity of OC1 for calcium channel subtypes was virtually screened in combination with computer-aided drug design. The fluorescence probe Fluo-3/AM was used to detect Ca~(2+) concentration in cells. Western blot analysis was performed to detect the effects of OC1 on the expression of phosphorylated calmodulin-dependent protein kinase Ⅱ(p-CaMKⅡ, Thr286) and synaptic vesicle-related proteins, and UPLC/Q Exactive MS was used to detect the effects of OC1 on ACh release in AD models. The effects of OC1 on acetylcholine esterase(AChE) activity in AD models were detected. The results showed that the differentially modified proteins in the model group and the OC1 treatment group were related to calcium channel activation at three levels: GO classification, KEGG pathway, and protein domain. The results of molecular docking revealed the dominant role of L-type calcium channels. Fluo-3/AM fluorescence intensity decreased under the presence of Ca~(2+) chelating agent ethylene glycol tetraacetic acid(EGTA), L-type calcium channel blocker verapamil, and N-type calcium channel blocker conotoxin, and the effect of verapamil was stronger than that of conotoxin. This confirmed that OC1 promoted extracellular Ca~(2+) influx mainly through its interaction with L-type calcium channel protein. In addition, proteomic analysis and Western blot results showed that the expression of p-CaMKⅡ and downstream vesicle-related proteins was up-regulated after OC1 treatment, indicating that OC1 acted on vesicle-related proteins by activating CaMKⅡ and participated in synaptic remodeling and transmitter release, thus affecting learning and memory. OC1 also decreased the activity of AChE and prolonged the action time of ACh in synaptic gaps.
Animals ; Rats ; Glucosides/administration & dosage* ; Acetylcholine/metabolism* ; Alzheimer Disease/genetics* ; PC12 Cells ; Phenols/chemistry* ; Neurotransmitter Agents/metabolism* ; Drugs, Chinese Herbal ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/genetics* ; Humans ; Phosphorylation/drug effects* ; Calcium/metabolism* ; Polyphenols

Objective To understand the current situation of human brain donation in Hebei Province by analyzing the basic information of Human Brain Bank samples of Hebei Medical University in order to provide basic data support for subsequent scientific research.Methods The samples collected from the Human Brain Bank of Hebei Medical University were analyzed(from December 2019 to February 2024),including gender,age,cause of death,as well as quality control data such as postmortem delay time,pH value of cerebrospinal fluid and and RNA integrity number and result of neuropathological diagnosis.Results Until February 2024,30 human brain samples were collected and stored in the Human Brain Bank of Hebei Medical University,with a male to female ratio of 9∶1.Donors over 70 years old accounted for 53％.Cardiovascular and cerebrovascular diseases(36.67％)and nervous system diseases(23.33％)accounted for a high proportion of the death causes.The location of brain tissue donors in Shijiazhuang accounted for 90％donations,and the others were from outside the city.The postmortem delay time was relatively short,90％within 12 hours and 10％more than 12 hours.69.23％of the brain samples had RNA integrity values greater than 6.Cerebrospinal fluid pH values ranged from 5.8 to 7.5,with an average value of 6.60±0.45.Brain weights ranged from 906-1496 g,with an average value of(1210.78±197.84)g.Three apolipoprotein E(APOE)alleles were detected including five genotypes(ε2/ε3,ε2/ε4,ε3/ε3,ε3/ε4,ε4/ε4).Eleven staining methods related to neuropathological diagnosis had been established and used.A total of 12 cases were diagnosed as neurodegenerative diseases(including Alzheimer's disease,Parkinson's disease,multiple system atrophy,corticobasal degeneration and progressive supranuclear palsy,etc.),accounting for 40％donated brains.The comorbidity rate of samples over 80 years old was 100％.Conclusion The summary and analyses of the data of brain donors in the Human Brain Bank of Hebei Medical University can reflect the current situation of the construction and operation of the brain bank in Hebei Province,and it can also be more targeted to understand and identify potential donors.Our information can provide reference for the construction of brain bank and provides more reliable materials and data support for scientific research.

A portable multi-wavelength spectral detector was developed for on-site,rapid and accurate detection of organic pollutants in surface water using ultraviolet light-emitting diodes(UV-LEDs)and the corresponding spectral detection method was built.By measuring the fluorescence spectrum and absorption light intensity and combining with the multi-wavelength spectral correlation calculation method to analyze the target,the developed detector was able to qualitatively and quantitatively detect organic pollutants that responded in the UV-light range of 260-370 nm.The proposed detector was used to detect polycyclic aromatic hydrocarbons(PAHs)and Rhodamine B.The linear ranges of anthracene and Rhodamine B in absorption mode were 10-100 and 8.5-100 mg/L,respectively.In fluorescence mode,the linear ranges for anthracene and Rhodamine B were 0.006-50 and 0.02-0.781 mg/L,correspondingly.The absorption/fluorescence concurrent mode could extend the detection ranges of anthracene and Rhodamine B to 0.006-100 and 0.02-100 mg/L,respectively.The recoveries of PAHs in surface water ranged from 97.4%to 105.1%for anthracene and 84.5%to 91.2%for anthracene,naphthalene,and pyrene in absorption and fluorescence modes,respectively.The method was accurate in both modes.The mixtures containing PAHs were identified by the proposed method under the optimized multi-wavelength spectral correlation calculation.The results demonstrated that the method could achieve a similarity of 75%or more when identifying two different concentrations of solutions containing a single or a mixture of targets within the linear concentration range of the targets.However,the similarity dropped to less than 25%when identifying two solutions of different substances.The proposed method had excellent recognition abilityof targets.The proposed detector and method combined fluorescence and absorption spectroscopy,which could expand the application of spectroscopy in the in situ rapid identification and detection of pollutants such as PAHs in surface water.

Objective:To evaluate the association between preoperative serum β 2-microglobulin (β 2MG) concentrations and postoperative delirium (POD) in elderly patients. Methods:The study selected patients who underwent knee or hip arthroplasty under spinal-epidural anesthesia on an elective basis at Qingdao Municipal Hospital from May 2021 to November 2022. The patients were divided into a POD group and a non-POD group based on the occurrence of POD. The study was conducted as part of the Perioperative Neurocognitive Impairment and Biomarkers Lifestyle Cohort, which was a nested case-control study. The study collected baseline data from two groups of patients and analyzed the differences between them. Logistic regression was used to identify the risk factors for POD. The stability of the regression model was tested using sensitivity analysis. The mediation model was used to examine whether cerebrospinal fluid (CSF) biomarkers mediated the relationship between β 2MG and POD. The receiver operating characteristic curve was drawn and the area under the curve was calculated to evaluate the accuracy of preoperative β 2MG concentrations and CSF biomarker concentration in predicting POD. Results:There were 57 cases in POD group and 449 cases in non-POD group. The results of logistic regression analysis showed that the increased β 2MG and CSF total tau protein (t-tau) concentrations were risk factors for POD, and the increased CSF β-amyloid 42 concentration was a protective factor for POD after adjustment for multiple confounders such as age, gender, education, Mini-Mental State Examination, history of hypertension and infusion volume ( P<0.05). The results of mediation analysis showed that the serum β 2MG′s effect on POD was partly mediated by t-tau (18.1%). The results of the receiver operating characteristic curve showed that the area under the curve of the β 2MG concentration combined with the CSF biomarker concentration was 0.742. Conclusions:Elevated preoperative serum β 2MG concentration is a risk factor for POD in elderly patients, and the relationship may be partly mediated by CSF t-tau.

Objective: To explore the balance of peripheral blood T helper 17 cells/regulatory T cell (Th17/Treg) ratio and the polarization ratio of M1 and M2 macrophages in lower extremity arteriosclerosis obliterans (ASO). Methods: A rat model of lower extremity ASO was established, and blood samples from patients with lower extremity ASO before and after surgery were obtained. ELISA was used to detect interleukin 6 (IL-6), IL-10, and IL-17. Real-time RCR and Western blot analyses were used to detect Foxp3, IL-6, IL-10, and IL-17 expression. Moreover, flow cytometry was applied to detect the Th17/Treg ratio and M1/M2 ratio. Results: Compared with the control group, the iliac artery wall of ASO rats showed significant hyperplasia, and the concentrations of cholesterol and triglyceride were significantly increased (P<0.01), indicating the successful establishment of ASO. Moreover, the levels of IL-6 and IL-17 in ASO rats were pronouncedly increased (P<0.05), while the IL-10 level was significantly decreased (P<0.05). In addition to increased IL-6 and IL-17 levels, the mRNA and protein levels of Foxp3 and IL-10 in ASO rats were significantly decreased compared with the control group. The Th17/Treg and M1/M2 ratios in the ASO group were markedly increased (P<0.05). These alternations were also observed in ASO patients. After endovascular surgery (such as percutaneous transluminal angioplasty and arterial stenting), all these changes were significantly improved (P<0.05). Conclusions: The Th17/Treg and M1/M2 ratios were significantly increased in ASO, and surgery can effectively improve the balance of Th17/Treg, and reduce the ratio of M1/M2, and the expression of inflammatory factors.

Small-molecule phenolic substances widely exist in animals and plants, and have some shared biological activities. The metabolism of phenylalanine and tyrosine in the human body, and especially the metabolism of catecholamine neurotransmitters, produces endogenous small-molecule phenols. Endogenous small-molecule phenolic substances are functionally related to the important physiological processes and the occurrence of mental diseases in humans and some animals, which are systematically sorts and summarized in this review. Integrating the previous experimental research and literature analysis on natural small-molecule phenols by our research group, the understanding of the hypothesis that "small-molecule phenol are pharmacological signal carriers" was deepened. Based on above, the concept of "phenolomics" was further proposed, analyzed the research direction and research content which can bring into the knowledge framework of phenolomics. The induction of phenolomics will provide wider perspectives on explaining the pharmacological mechanism of drugs, discovering new drug targets, and finding biomarkers of mental diseases.